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What is ESMC?
ESMC marks the latest innovation in the ESM series of protein language models, advancing the understanding of representation learning in protein biology. By training on an enormous dataset of billions of evolutionary sequences, it effectively captures representations that provide insights into the mechanistic aspects of protein structure and function. Utilizing a transformer architecture, the model prioritizes sequences as its main input and is trained on a dataset that includes up to 6 billion proteins. ESMC is designed for a range of applications within protein science, including structure prediction, functional annotation, protein design, and the investigation of evolutionary relationships among proteins. Furthermore, it has the ability to generate new proteins from partial sequences, structures, or specific functional requirements, which allows researchers to explore novel possibilities in protein design and biological research. The model is readily accessible through the Biohub Platform, enabling users to interact with it via an API and the ESM Python package, which offers quickstart resources for installation, API key generation, and connection to the platform, thus ensuring a user-friendly experience. This ease of access not only promotes wider participation in protein research but also fosters collaborative efforts across the scientific community, ultimately driving further advancements in the field. With its capabilities, ESMC opens new doors for innovation and discovery in protein science.
What is Causaly?
Leverage the power of artificial intelligence to expedite the shift from laboratory experiments to the launch of innovative therapies. By reducing literature review time from months to just minutes, researchers can achieve an impressive boost in productivity, potentially increasing efficiency by up to 90%. This streamlined approach not only helps in minimizing distractions but also enhances search accuracy, making it easier to navigate the vast realm of scientific literature. Such advancements not only conserve time but also reduce bias, increasing the chances of uncovering revolutionary insights. Dive into the complexities of disease biology and participate in advanced target identification with ease. Causaly's sophisticated knowledge graph consolidates data from numerous publications, allowing for comprehensive and objective scientific research. Effortlessly navigate the complex web of biological cause-and-effect relationships without needing extensive expertise. Gain access to a wide range of scientific documents while uncovering connections that may have been previously missed. Causaly's powerful AI technology processes millions of biomedical articles, leading to better decision-making and improved research results, ultimately fostering a more knowledgeable and innovative scientific community. By embracing these advanced tools, researchers can not only refine their methodologies but also significantly enhance their impact on the field of medicine, paving the way for future breakthroughs. Embracing AI in research practices sets the stage for a new era of medical advancements and collaborative scientific exploration.
Integrations Supported
Biohub
Python
API Availability
Has API
API Availability
Has API
Pricing Information
Free
Free Version
Free Trial Offered?
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Biohub
Date Founded
2016
Company Location
United States
Company Website
biohub.ai/models/esmc
Company Facts
Organization Name
Causaly
Date Founded
2018
Company Location
United Kingdom
Company Website
www.causaly.com